Multiagent deep reinforcement learning for vehicular computation offloading in IoT
X Zhu, Y Luo, A Liu, MZA Bhuiyan… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The development of the Internet of Things (IoT) and intelligent vehicles brings a comfortable
environment for users. Various emerging vehicular applications using artificial intelligence …
environment for users. Various emerging vehicular applications using artificial intelligence …
A deep reinforcement learning based computation offloading with mobile vehicles in vehicular edge computing
Vehicular edge networks involve edge servers that are close to mobile devices to provide
extra computation resource to complete the computation tasks of mobile devices with low …
extra computation resource to complete the computation tasks of mobile devices with low …
Deep-reinforcement-learning-based offloading scheduling for vehicular edge computing
Vehicular edge computing (VEC) is a new computing paradigm that has great potential to
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …
Deep reinforcement learning for vehicular edge computing: An intelligent offloading system
The development of smart vehicles brings drivers and passengers a comfortable and safe
environment. Various emerging applications are promising to enrich users' traveling …
environment. Various emerging applications are promising to enrich users' traveling …
Deep reinforcement learning for offloading and resource allocation in vehicle edge computing and networks
Mobile Edge Computing (MEC) is a promising technology to extend the diverse services to
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …
Dynamic edge computation offloading for internet of vehicles with deep reinforcement learning
Recent developments in the Internet of Vehicles (IoV) enabled the myriad emergence of a
plethora of data-intensive and latency-sensitive vehicular applications, posing significant …
plethora of data-intensive and latency-sensitive vehicular applications, posing significant …
Com-DDPG: task offloading based on multiagent reinforcement learning for information-communication-enhanced mobile edge computing in the internet of vehicles
H Gao, X Wang, W Wei, A Al-Dulaimi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The emergence of the Internet of Vehicles (IoV) introduces challenges regarding
computation-intensive and time-sensitive related services for data processing and …
computation-intensive and time-sensitive related services for data processing and …
Unmanned-aerial-vehicle-assisted computation offloading for mobile edge computing based on deep reinforcement learning
H Wang, H Ke, W Sun - IEEE Access, 2020 - ieeexplore.ieee.org
Users in heterogeneous wireless networks may generate massive amounts of data that are
delay-sensitive or require computation-intensive processing. Owing to computation ability …
delay-sensitive or require computation-intensive processing. Owing to computation ability …
Distributed computation offloading method based on deep reinforcement learning in ICV
With the rapid development of Intelligent Connected Vehicles (ICVs), more effective
computation resources optimization schemes in task scheduling are exactly required for …
computation resources optimization schemes in task scheduling are exactly required for …
Deep reinforcement learning-based adaptive computation offloading for MEC in heterogeneous vehicular networks
H Ke, J Wang, L Deng, Y Ge… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The vehicular network needs efficient and reliable data communication technology to
maintain low latency. It is very challenging to minimize the energy consumption and data …
maintain low latency. It is very challenging to minimize the energy consumption and data …
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